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Systematic Review of Literature for Smartphones Technology Acceptance Using Unified Theory of Acceptance and Use of Technology Model (UTAUT)

DOI: 10.4236/sn.2023.122002, PP. 29-44

Keywords: Systematic Review of Literature, UTAUT, Technology Acceptance, Smartphone, Education Technology, Technology Acceptance

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Abstract:

Systematic Review and Meta-analysis are techniques which attempt to associate the findings from similar studies and deliver quantitative summaries of the research literature[1]. The Systematic review of research literature identifies the common research methods, research design, sample size, parameters used, survey instruments, etc. used by the group of researchers. This study intends to fulfill this purpose in order to identify common research mythologies, dependent variables, sample sizes, moderators and mediators used in the field of analysing technology adoption based studies that utilizes the UTAUT2 model. This research collected over 59 published articles and conducted descriptive analytics. The results have revealed performance expectancy/perceived usefulness, trust and habit as the best predictors of consumer behavioural intentions towards the adoption of mobile application. Behavioural intention was the best predictor of use behaviour among the 57 articles selected. 274 was the mean sample size of research with 25 mean questionnaire items. SPSS and AMOS were the most common softwares used in all 57 studies, and 32 of those studies used UTAUT1 model while 14 researches incorporated the UTAUT2 model. There were also two promising predictors such as perceived risk on behavioural intention and habit on use behaviour.

References

[1]  Morris, S.B. (2007) Book Review. In: Hunter, J.E. and Schmidt, F.L., Eds., Methods of Meta-Analysis: Correcting Error and Bias in Research Findings, Sage Publications, Thousand Oaks, 184-187.
https://doi.org/10.1177/1094428106295494
[2]  Wolf, F.M. (1986) Meta-Analysis: Quantitative Methods for Research Synthesis. Sage Publication, Thousand Oaks.
[3]  Schmidt, F.L. and Hunter, J.E. (2004) Methods of Meta-Analysis: Correcting Error and Bias in Research Findings. 3rd Edition, Sage Publications, Thousand Oaks.
[4]  Dwivedi, Y.K., Shareef, M.A., Simintiras, A.C., Lal, B. and Weerakkody, V. (2016) A Generalised Adoption Model for Services: A Cross-Country Comparison of mobile Health (M-Health). Government Information Quarterly, 33, 174-187.
https://doi.org/10.1016/j.giq.2015.06.003
[5]  Van Houwelingen, C.T., Barakat, A., Best, R., Boot, W.R., Charness, N. and Kort, H.S. (2015) Dutch Nurses’ Willingness to Use Home Telehealth: Implications for Practice and Education. Journal of Gerontological Nursing, 41, 47-56.
https://doi.org/10.3928/00989134-20141203-01
[6]  Stanley, T.D. (2001) Wheat from Chaff: Meta-Analysis as Quantitative Literature Review. The Journal of Economic Perspectives, 15, 131-150.
https://doi.org/10.1257/jep.15.3.131
[7]  Admiraal, W., Lockhorst, D., Smit, B. and Weijers, S. (2013) The Integrative Model of Behavior Prediction to Explain Technology Use in Post-Graduate Teacher Education Programs in the Netherlands. International Journal of Higher Education, 2, 172-178.
https://doi.org/10.1257/jep.15.3.131
[8]  Abu-Al-Aish, A. and Love, S. (2013) Factors Influencing Students’ Acceptance of M-Learning: An Investigation in Higher Education. The International Review of Research in Open and Distributed Learning, 14, 83-107.
https://doi.org/10.19173/irrodl.v14i5.1631
[9]  Yang, S. (2013) Understanding Undergraduate Students’ Adoption of Mobile Learning Model: A Perspective of the Extended UTAUT2. Journal of Convergence Information Technology, 8, 969-979.
[10]  Yang, P., Chiang, J., Liu, J., Wen, Y. and Chuang, K. (2010) An Efficient Cloud for Wellness Self-Management Devices and Services. Fourth International Conference on Genetic and Evolutionary Computing (ICGEC), Shenzhen, 13-15 December 2010, 767-770.
[11]  Jambulingam, M. (2013) Behavioural Intention to Adopt Mobile Technology among Tertiary Students. World Applied Sciences Journal, 22, 1262-1271.
[12]  Faaeq, M.K., Alqasa, K. and Al-Matari, E.M. (2015) Technology Adoption and Innovation of E-Government in Republic of Iraq. Asian Social Science, 11, 135-145.
https://doi.org/10.5539/ass.v11n3p135
[13]  Nassuora, A.B. (2012) Students Acceptance of Mobile Learning for Higher Education in Saudi Arabia. American Academic & Scholarly Research Journal, 4, 24-30.
[14]  Wang, M., Shen, R., Novak, D. and Pan, X. (2009) The Impact of Mobile Learning on Students’ Learning Behaviours and Performance: Report from a Large Blended Classroom. British Journal of Educational Technology, 40, 673-695.
https://doi.org/10.1111/j.1467-8535.2008.00846.x
[15]  Jairak, K., Praneetpolgrang, P. and Mekhabunchakij, K. (2009) An Acceptance of Mobile Learning for Higher Education Students in Thailand. The Sixth International Conference on eLearning for Knowledge-Based Society, Thailand, 17-18 December 2009, 8.
[16]  Liu, L., Miguel C.A., Rincon, R.A., Buttar, V., Ranson, Q. and Goertzen, D. (2015) What Factors Determine Therapists’ Acceptance of New Technologies for Rehabilitation—A Study Using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disability and Rehabilitation, 37, 447-455.
https://doi.org/10.3109/09638288.2014.923529
[17]  Wu, Y.L., Tao, Y.H. and Yang, P.C. (2007) Using UTAUT to Explore the Behavior of 3G Mobile Communication Users. IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, 2-4 December 2007, 199-203.
https://doi.org/10.1109/IEEM.2007.4419179
[18]  Raman, A. and Don, Y. (2013) Preservice Teachers’ Acceptance of Learning Management Software: An Application of the UTAUT2 Model. International Education Studies, 6, 157-164.
https://doi.org/10.5539/ies.v6n7p157
[19]  Yu, C. (2012) Factors Affecting Individuals to Adopt Mobile Banking: Empirical Evidence from the UTAUT Model. Journal of Electronic Commerce Research, 13, 104-121.
[20]  Moran, M., Hawkes, M. and Gayar, O.E. (2010) Tablet Personal Computer Integration in Higher Education: Applying the Unified Theory of Acceptance and Use Technology Model to Understand Supporting Factors. Journal of Educational Computing Research, 42, 79-101.
https://doi.org/10.2190/EC.42.1.d
[21]  Zhang, X. and Venkatesh, V. (2018) From Design Principles to Impacts: A Theoretical Framework and Research Agenda. AIS Transactions on Human-Computer Interaction, 10, 105-128.
https://doi.org/10.17705/1thci.00106
[22]  Carlsson, C., Carlsson, J., Hyvonen, K., Puhakainen, J. and Walden, P. (2006) Adoption of Mobile Devices/Services-Searching for Answers with the UTAUT. Proceedings of the 39th Annual Hawaii International Conference on System Sciences, Hawaii, 4-7 January 2006, 132a.
https://doi.org/10.1109/HICSS.2006.38
[23]  Sundaravej, T. (2010) Empirical Validation of Unified Theory of Acceptance and Use of Technology Model. Journal of Global Information Technology Management, 13, 5-27.
https://doi.org/10.1080/1097198X.2010.10856507
[24]  Williams, B., Brown, T. and Onsman, A. (2012) Exploratory Factor Analysis: A Five-Step Guide for Novices. Australasian Journal of Paramedicine, 8, 1-13.
https://doi.org/10.33151/ajp.8.3.93
[25]  Abdulwahab, L., and Zulkhairi, M. (2012) Modeling the Determinants and Gender, Age and ethnicity Difference in Telecommunication Centre Acceptance. Research Journal of Information Technology, 4, 85-105.
https://doi.org/10.3923/rjit.2012.85.105
[26]  Alrawashdeh, T., Muhairat, M., and Alqatawnah, S. (2012) Factors Affecting Acceptance of Web-Based Training System: Using Extended UTAUT and Structural Equation Modeling. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), 2, 45-54.
https://doi.org/10.5121/ijcseit.2012.2205
[27]  Pheeraphuttharangkoon, S., Choudrie, J., Zamani, E. and Giaglis, G. (2014) Investigating the Adoption and Use of Smartphones in the UK: A Silver-Surfers Perspective. University of Hertfordshire, Hertfordshire.
https://uhra.herts.ac.uk/handle/2299/13507
[28]  Shin, D.H., Shin, Y.J., Choo, H. and Beom, K. (2011) Smartphones as Smart Pedagogical Tools: Implications for Smartphones as U-Learning Devices. Computers in Human Behavior, 27, 2207-2214.
https://doi.org/10.1016/j.chb.2011.06.017
[29]  Pitchayadejanant, K. (2011) Intention to Use of Smartphone in Bangkok Extended UTAUT Model by Perceived Value. Proceedings of the International Conference on Management Proceedings, Penang, June 2011, 160-172.
[30]  Chen, J.V., Yen, D.C. and Chen, K. (2009) The Acceptance and Diffusion of the Innovative Smart Phone Use: A Case Study of a Delivery Service Company in Logistics. Information & Management, 46, 241-248.
https://doi.org/10.1016/j.im.2009.03.001

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